Evidence map›Paper›PMID 36340828›Full record

ArticleIPEM-translation

Telemedicine and health disparities: Association between patient characteristics and telemedicine, in-person, telephone and message-based care during the COVID-19 pandemic.

Ling Tong, Ben George, Bradley H Crotty, Melek Somai, Bradley W Taylor, Kristen Osinski, Jake Luo

Open access · goldAbstract read
In one paragraph

Article in IPEM-translation. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 2 pooled it
8.0field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 2 syntheses or guidelines pooled it, 42 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
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  4. Review
  5. Article
  6. Article
  7. Article
  8. State Medicaid Telehealth Policies and Rates of Alcohol and Substance Use Treatment at Federally Qualified Health Centers: Does Modality Matter?Telemedicine journal and e-health : the official journal of the American Telemedicine Association · 2026
    Article
  9. Review
  10. Review
  11. Article
  12. Article
  13. Digital health equity frameworks and key concepts: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2025
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 1 country.

Ling TongUniversity of Wisconsin-Milwaukee, Department of Health Informatics and Administration, United States.
Ben GeorgeMedical College of Wisconsin, Clinical and Translational Science Institute of Southeastern Wisconsin, Froedtert Hospital, United States.
Bradley H CrottyMedical College of Wisconsin, Clinical and Translational Science Institute of Southeastern Wisconsin, United States.
Melek SomaiMedical College of Wisconsin, Clinical and Translational Science Institute of Southeastern Wisconsin, United States.
Bradley W TaylorMedical College of Wisconsin, Clinical and Translational Science Institute of Southeastern Wisconsin, United States.
Kristen OsinskiMedical College of Wisconsin, Clinical and Translational Science Institute of Southeastern Wisconsin, United States.
Jake LuoUniversity of Wisconsin-Milwaukee, Department of Health Informatics and Administration, United States.
Medical College of Wisconsin · USUniversity of Wisconsin–Milwaukee · USFroedtert Hospital · US

Funding

Clinical and Translational Science AwardUL1TR001436 · NCATS · MEDICAL COLLEGE OF WISCONSIN · PI FREED, JULIE K · 2015 to 2025
$47.5M
NCATS NIH HHS UL1 TR001436
6 · The paper itself

Abstract

Telemedicine has been an essential form of care since the onset of the COVID-19 pandemic. However, telemedicine may exacerbate disparities for populations with limited digital literacy or access, such as older adults, racial minorities, patients of low income, rural residences, or limited English proficiency. From March 2020 to March 2022, this retrospective cohort study analyzed the use of in-person, phone/message, and telemedical care at a single tertiary care center in an oncology department. We investigated the association between economic, racial, ethnic, socioeconomic factors and forms of care, including in-person visits, telemedicine-based visits, and telephone/messages. The study results show that telemedicine utilization is lower among patients 65 and older, female patients, American Indian or Alaska Native patients, uninsured patients, and patients who require interpreters during clinical visits. As a result, it is unlikely that telemedicine will provide equal access to clinical care for all populations. On the other hand, in-person care utilization remains low in low-income and rural-living patients compared to the general population, while telephone and message use remains high in low-income and rural-living patients. We conclude that telemedicine is currently unable to close the utilization gap for populations of low socioeconomic status. Patients with low socioeconomic status use in-person care less frequently. For the disadvantaged, unusually high telephone or message utilization is unlikely to provide the same quality as in-person or telemedical care. Understanding the causes of disparity and promoting a solution to improve equal access to care for all patients is critical.

Indexed as

Health DisparityOncologyRemote CareTelemedicine

Identifiers

PMID36340828
PMCPMC9617798
OpenAlexW4307955471

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.